Who Are Your At-Risk Students? Using Data Mining to Target Intervention Efforts

Wednesday, October 16 | 11:30AM–12:20PM | Meeting Room 211A/B
Session Type: Professional Development
Improve targeted intervention by building a model to identify and classify at-risk students using data at your institution—and do it in-house with available data-mining tools. Find out how we did this at New York Institute of Technology and how you can do it as well.

OUTCOMES:
Gain an understanding of the complete life cycle of the At-Risk Student Identification Model. | Learn about the methodology and technologies used to create the model. | Understand how to initiate a similar model.

Presenters

  • Lalitha Agnihotri

    Senior Learning and Data Scientist, McGraw-Hill Education
  • Niyazi Bodur

    CIO, Binghamton University

Resources & Downloads